Data driven biology
This priority falls under the enabling theme 'Exploiting New Ways of Working'.
World-class bioscience is critically dependent on new computational technologies, methodologies and resources. This priority aims to encourage research that will yield the next-generation of these 'new ways of working'. Projects should focus on underpinning and enabling one of our strategic research priorities (agriculture and food security, industrial biotechnology and bioenergy, bioscience for health) or have potential generic utility across one or more broad areas of the biosciences.
The data driven biology priority aims to encourage the development of the bioinformatics tools and computational approaches that are required to extract value and generate new biological understanding from the huge volume and diversity of bioscience data now available and so underpin and enable biological research as it continues to evolve as a data intensive discipline.
The complexity and scale of biological data is continually increasing and this places demands on the ability of biologists to manage and analyse data. Innovative computational approaches are needed for the integration, analysis and interpretation of new and repurposed biological data to enable bioscientists to gain value and scientific leads from the enormous quantities and diversity of data available.
For a project to address the data driven biology priority a significant focus of the work must involve the initiation or further development of advanced computational tools, resources or methodologies relevant to our remit. Projects may develop entirely new applications, employ cutting-edge computational methods to better exploit data resources, or provide innovative functionality and improvements to an existing computational tool or resource.
Under this priority, examples of broad data driven research challenges that projects might address include:
- Integration, interrogation and analysis of large or complex datasets such as those generated by multiple 'omics technologies
- Investigating links between phenotypic traits and variation in biological systems or processes
- Extracting quantitative information from large or complex image sets
- Supporting knowledge discovery from biological data, for example: developing platforms for data sharing and integration, or new data visualisation approaches
The data driven biology priority also seeks to encourage exploitation of advanced computing technologies and approaches, for example: semantic computing, high performance computing, cloud computing and text-mining. Activities that support the maturation of the biological data landscape, such as the development of community data standards, ontologies and data management tools, or enhancement and maturation of existing research software, are also incorporated within the priority.
Data driven biology complements the technology development priority by providing a focus on the computational tools, resources and methods that are essential to derive maximum value from bioanalytical or biological-based technologies. Projects that combine computational approaches with the development of data-generating bioanalytical or biological technologies, for example to enhance analysis or automate metadata generation and manipulation, are also covered by this priority.
Proposals in data driven biology (informatics tools development) should describe how they will fulfil (an) unmet need(s) in the biosciences. It is expected that new informatics tools and resources developed under this priority area will be designed, as much as possible and practical, with end users in mind. Evidence of end-user engagement may be provided in support of applications.
Many of the most exciting advances in biology are likely to occur at the interface with other disciplines through truly multidisciplinary approaches. Proposals involving strong multidisciplinary partnerships between bioscientists and researchers in the physical sciences, engineering and information technology disciplines are therefore particularly welcome.
Projects focused primarily on the use of an existing tool or minor developments of existing tools do not fall within this priority area.
Proposals should comply with our data sharing policy (see related links). Proposals developing informatics tools should make such tools available to the wider user and developer community with as few restrictions as possible, ideally using open source best practices (e.g. Creative Commons or Open Source Initiative recommended licences). However, we recognise that, at times, the creators' intellectual property rights may need to be protected before any sharing takes place. Such protection should not unduly delay the release of any data or tools arising from BBSRC funding.
It is expected that proposals in the area of 'data driven biology' will provide tools, resources and methodologies of potential application to broad communities in the biosciences. As well as enabling world class bioscience proposals they may have particular relevance to one or more of our other Council-wide strategic priorities.